541 件 ・ 関連度順
概要と使いどころ
Implement project-consistent UI through page classification, bounded references, semantic tokens, skeleton-first delivery, and responsive screenshot QA. Use for frontend redesigns, dashboards, forms, settings, mobile pages, screenshot recreation, visual polish, or generic-looking generated UI.
日本語の概要は準備中です。原文の説明を表示しています。
Use when designing, redesigning, or improving a frontend interface in Angular, React, or Blazor. Use for landing pages, dashboards, components, forms, and responsive layouts that must work mobile-first and then scale to desktop.
日本語の概要は準備中です。原文の説明を表示しています。
Use when the user wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI tasks.
日本語の概要は準備中です。原文の説明を表示しています。
Raw mechanical interfaces fusing Swiss typographic print with military terminal aesthetics. Rigid grids, extreme type scale contrast, utilitarian color, analog degradation effects. For data-heavy dashboards, portfolios, or editorial sites that need to feel like declassified blueprints.
日本語の概要は準備中です。原文の説明を表示しています。
Analytics de produto — PostHog, Mixpanel, eventos, funnels, cohorts, retencao, north star metric, OKRs e dashboards de produto.
日本語の概要は準備中です。原文の説明を表示しています。
Builds SOC performance metrics and KPI tracking dashboards measuring Mean Time to Detect (MTTD), Mean Time to Respond (MTTR), alert quality ratios, analyst productivity, and detection coverage using SIEM data. Use when SOC leadership needs operational visibility, continuous improvement tracking, or executive-level reporting on security operations effectiveness.
日本語の概要は準備中です。原文の説明を表示しています。
Builds real-time incident response dashboards in Splunk, Elastic, or Grafana to provide SOC analysts and leadership with situational awareness during active incidents, tracking affected systems, containment status, IOC spread, and response timeline. Use when IR teams need unified visibility during incident coordination and post-incident reporting.
日本語の概要は準備中です。原文の説明を表示しています。
Builds a structured vulnerability scanning workflow using tools like Nessus, Qualys, and OpenVAS to discover, prioritize, and track remediation of security vulnerabilities across infrastructure. Use when SOC teams need to establish recurring vulnerability assessment processes, integrate scan results with SIEM alerting, and build remediation tracking dashboards.
日本語の概要は準備中です。原文の説明を表示しています。
PumpOS — static HTML/CSS/JS web desktop for the Pump SDK with 169 Pump-Store apps, live token dashboards, interactive DeFi tools, PWA support, and Vercel deployment.
日本語の概要は準備中です。原文の説明を表示しています。
Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.
日本語の概要は準備中です。原文の説明を表示しています。
Streamlit Web application development expert skill. Provides guidance on OIDC authentication (st.login/st.logout/st.user), secrets management, data visualization with Plotly/Altair, performance optimization with caching, and modern Streamlit features (v1.42-1.52+). Use this skill when building Streamlit apps, implementing user authentication, creating data dashboards, or optimizing app performance. Triggers include "streamlit app", "st.login", "data dashboard", "streamlit authentication", "streamlit visualization".
日本語の概要は準備中です。原文の説明を表示しています。
Load for .NET observability changes involving structured logs/Loki, Prometheus metrics, OpenTelemetry traces, exception handling, correlation IDs, dashboards, alerts, or production error diagnosis; not for ordinary business validation errors.
日本語の概要は準備中です。原文の説明を表示しています。
Read the system-architect map: a deterministic catalog of everything the setup is made of (vault, import scripts, scheduled tasks, MCP servers, SQLite databases, hooks, skills, dashboards), what is healthy and what fell off. Consult it before changing shared infrastructure and re-scan after. Triggers: "/arch", "/arch broken", "/arch scan", "what broke in the system".
日本語の概要は準備中です。原文の説明を表示しています。
Submission-grade remote-sensing Nature/high-impact journal figure workflow for Python or R. Use whenever the user asks to create, revise, audit, or polish manuscript figures, multi-panel scientific plots, map-led composites, remote-sensing image plates, sensor/product workflow figures, validation/error/uncertainty panels, or journal-ready SVG/PDF/TIFF outputs, especially for Nature-family, Remote Sensing of Environment, ISPRS, IEEE TGRS, or other high-impact venues. Before plotting, define the figure's conclusion, evidence logic, export needs, and review risks. If the user has not chosen Python or R, ask "Python or R?" and stop. Use only the selected backend for figure generation, previewing, exporting, and QA. Supports matplotlib/seaborn and ggplot2/patchwork/ComplexHeatmap. Not for dashboards or Illustrator/Figma-first infographics. Also trigger on general academic-writing figure needs even without the word "Nature", such as making figures/plots for a paper, scientific/academic plotting, data visualization for a manuscript, and Chinese phrasings like 遥感论文配图、学术写作配图、科研绘图、科研作图、地图出图、论文图表、可视化.
日本語の概要は準備中です。原文の説明を表示しています。
Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.
日本語の概要は準備中です。原文の説明を表示しています。
Use when the user asks to "generate an SEO report", "出月报", "set SEO alerts", or "排名掉了提醒我"; two modes — report builds multi-metric traffic/ranking/authority/content dashboards, and alert configures threshold notifications for future ranking, traffic, technical, backlink, competitor, and AI-visibility changes. Not for raw position-by-position deltas — use rank-tracker. SEO报告/绩效仪表盘/SEO预警/排名监控
日本語の概要は準備中です。原文の説明を表示しています。
Marketing analytics and data-driven optimization for B2B SaaS campaigns. Use this skill when analyzing marketing performance, optimizing conversion rates, running A/B tests, conducting customer research, creating marketing dashboards, building attribution models, analyzing funnel metrics, or storytelling with data. Also triggers on: marketing ops, performance analytics, CRO, A/B testing, data storytelling, customer insights, tracking plan, event taxonomy, UTM taxonomy, GA4 audit, consent mode, instrumentation contract, sample size calculation, minimum detectable effect, test duration, not enough traffic to A/B test, statistical significance, Bayesian vs frequentist, sample ratio mismatch, experiment feasibility, martech stack, marketing tech stack audit, tool consolidation, build vs buy, vendor evaluation, shadow IT tools, ESP/CRM/platform migration, switching cost, cutover plan, suppression list migration, data portability, customer interviews, survey design, sampling frame, non-response bias, how many people should I interview, thematic saturation, voice of customer, jobs-to-be-done, buyer persona research, is this finding real, data enrichment, which enrichment provider should we buy, waterfall enrichment, contact data quality, match rate, our list data is bad, email verification, catch-all domain, accept-all, bounce rate from bad data, B2B data decay, how often should we re-verify contacts, ZoomInfo vs Apollo vs Clearbit evaluation, cost per usable record, where did this list come from, GDPR Article 14 notice, purchased list compliance, suppression screening, TAM list building, demand planning, marketing plan, how many leads do we need, what pipeline target should marketing carry, funnel model, top-down vs bottom-up plan, plan of record, annual marketing planning, quarterly planning, pipeline coverage we have to create, sales cycle lag, our leads cannot close this quarter, carry-in pipeline, scenario planning, conservative moderate aggressive forecast, stretch target, reforecast, re-forecast triggers, assumption register, capacity ceiling, addressable audience ceiling, marginal cost per lead, blended CPL is wrong, we missed plan and nobody knows why.
日本語の概要は準備中です。原文の説明を表示しています。
Client reporting, quality assurance, and financial operations management. Handles KPI frameworks, compliance audits, budget tracking, and launch checklists. Use when: managing client dashboards, ensuring brand compliance, conducting QA reviews, tracking marketing spend, ensuring GDPR/CAN-SPAM compliance, proofreading deliverables. Also triggers on: client reporting, QA, quality assurance, brand compliance, marketing budget, financial tracking, legal compliance, GDPR, CAN-SPAM, proofreading, launch checklist
日本語の概要は準備中です。原文の説明を表示しています。
Create an Estuary derivation that continuously aggregates metrics (daily totals, running counts, min/max, lifetime revenue) using reduction annotations. Use for real-time dashboards, continuous materialised views, and replacing batch ETL aggregations with streaming. Derivations add complexity and cost — confirm the user wants a derivation before reaching for this. Use when user says "aggregation derivation", "derivation to sum daily totals", "running-count derivation", "transformation for min/max per group", "derive lifetime metrics", "aggregate-by-date derivation", or "real-time-dashboard derivation".
日本語の概要は準備中です。原文の説明を表示しています。
Generative UI (GenUI) for Flutter using AI models like Google Gemini, Anthropic Claude, or OpenAI via the genui package. Use this skill when building dynamic AI-driven interfaces, conversational UI flows, server-rendered screen layouts, LLM-powered dashboards, chat-based UI generation, or implementing prompt-to-UI systems. Supports AI-generated widgets, reactive data binding, ContentGenerator integration, and A2uiMessageProcessor for real-time UI updates from AI responses. Ideal for apps where UI structure is determined by AI/LLM output rather than hardcoded layouts.
日本語の概要は準備中です。原文の説明を表示しています。
システムとアプリケーションメトリクスのリアルタイム可視化のための本番環境Grafanaダッシュボードを作成・管理します。モニタリングダッシュボードの構築、メトリクスの可視化、運用可観測性インターフェースの作成時に使用します。
Master modern business analysis with AI-powered analytics, real-time dashboards, and data-driven insights. Build comprehensive KPI frameworks, predictive models, and strategic recommendations.
日本語の概要は準備中です。原文の説明を表示しています。
Use when the user wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI tasks.
日本語の概要は準備中です。原文の説明を表示しています。
This skill is for interface design — dashboards, admin panels, apps, tools, and interactive products. NOT for marketing design (landing pages, marketing sites, campaigns).
日本語の概要は準備中です。原文の説明を表示しています。